From Emails to ERP Transactions: AI-Powered Order Processing for Unstructured Requests

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Quick Snapshot

Technostacks built an AI-powered order processing layer that sits between a company’s unstructured business requests and its ERP. Using a large language model and document AI, the solution reads orders and requests arriving by email, PDF, or chat, extracts structured details, customer, material, quantity, location, and delivery date, and validates them against ERP master data before any transaction is created. A business-rule engine applies organizational controls, and only validated requests become sales orders, purchase requests, or service requests through the ERP API. The result is a governed bridge between human language and structured ERP processes, not a chatbot bolted onto an ERP screen.

Brief

The client received a high volume of business requests through emails, PDFs, and messages. A sales rep might email, “Please create an order for 500 units of Product X for ABC Industries and deliver it to our Pune warehouse.” Everything needed to create that order already existed inside the ERP, yet someone still had to read the request, find the right customer and material, verify pricing and availability, and key it all in. This created unnecessary manual work and repeated opportunities for error.

Technostacks introduced an AI-powered order processing layer that translates human language into controlled ERP transactions. The distinction is deliberate: the LLM handles the unstructured language, while the ERP remains responsible for customer, material, pricing, inventory, and transaction validation.

SAP has identified generating sales orders from unstructured information as one of the prominent AI use cases among its Indian customers, underlining how common and costly this manual gap has become.

Challenges

Manual Re-Entry of Existing Data

Staff spent time keying in information that already existed inside the ERP, simply because it arrived as free text rather than structured data.

Error-Prone Order Creation

Manually reading requests and matching them to the right customer, material, and price introduced mistakes that surfaced downstream in fulfilment and billing.

Scattered Input Channels

Requests arrived via email, PDF, and chat in inconsistent formats, making standardized processing difficult.

Slow Request-to-Transaction Cycle

Every request waited on a person to interpret and enter it, adding delay between the customer’s request and a live ERP transaction.

Solution

Technostacks designed an AI-powered order-processing layer positioned between the user’s unstructured request and the ERP, translating natural language into validated transactions rather than asking an LLM to “create an ERP order” directly.

Document AI + LLM Extraction

The layer reads requests arriving as email, PDF, or chat and uses a large language model with document AI to interpret intent and extract structured fields: customer, material, quantity, location, and requested delivery date.

ERP Master-Data Validation

Every extracted value is validated against real ERP master data, customer records, material catalog, pricing, and inventory, so a transaction is only ever built from information the ERP recognizes.

Business-Rule Engine

Organizational rules and approval logic are applied before creation, keeping the process controlled and consistent with how the business actually operates.

Controlled Transaction Creation

Only after validation does the system create the relevant transaction through the ERP API, with exceptions routed for human review, keeping people in control of anything ambiguous.

How It Works

The order processing layer runs as a controlled pipeline, from an unstructured message to a validated ERP transaction.

Where It Extends

The same architecture, read, extract, validate, apply rules, create, applies well beyond sales orders:

Technologies Used

Large Language Model (LLM)

Document AI / Intelligent Document Processing

Entity Extraction (NLP)

ERP Master-Data Validation

Business-Rule Engine

Human-in-the-Loop Review

Exception Queue

ERP API Integration

Impact

The AI-powered order processing layer is designed to deliver measurable gains across effort, speed, and accuracy:

Conclusion

Technostacks turned a manual, error-prone re-entry process into a governed AI-powered order processing workflow that reads unstructured requests, validates them against the ERP, and creates the right transaction automatically. By separating the roles, the LLM interprets language, the ERP owns validation, and the solution captures the value of AI without handing it control of business-critical data.

The model is simple: human language in, ERP transaction out. With one extensible architecture spanning sales orders, purchase requests, customer service, expense processing, and vendor requests, the client now has a practical foundation for applying AI across every process that starts with an unstructured message.

Ready to Turn Your Inbox Into ERP Transactions?

Whether orders and requests arrive by email, PDF, or chat, Technostacks can build an AI layer that reads them, validates them against your ERP, and creates the transaction, with your team in control of every exception.

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